This monograph presents a framework for optimum design of timetables to maximise schedule robustness and minimise resource deployment, especially for large railway networks, wherein the problem has been formulated as a multi-objective non-linear model. The monograph?s contribution is the formulation of methods to reduce the problem size to computationally manageable proportions, and thus enable planners to undertake network-wide optimisation studies. The monograph demonstrates that the design of timetables can be spread over a canvas incorporating not only over the entire railway network, thus enabling study of the mutual interactions across the network, but also involving the optimisation of crew and rolling stock in the purview of the model. This can thus emulate the planning process more truthfully, wherein piecemeal optimisations are of little import. This monograph should be especially useful for researchers engaged in problems pertaining to railway networks, railway network planners, railway decision support software developers or one interested in industrial applications of operations research.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
This monograph presents a framework for optimum design of timetables to maximise schedule robustness and minimise resource deployment, especially for large railway networks, wherein the problem has been formulated as a multi-objective non-linear model. The monograph?s contribution is the formulation of methods to reduce the problem size to computationally manageable proportions, and thus enable planners to undertake network-wide optimisation studies. The monograph demonstrates that the design of timetables can be spread over a canvas incorporating not only over the entire railway network, thus enabling study of the mutual interactions across the network, but also involving the optimisation of crew and rolling stock in the purview of the model. This can thus emulate the planning process more truthfully, wherein piecemeal optimisations are of little import. This monograph should be especially useful for researchers engaged in problems pertaining to railway networks, railway network planners, railway decision support software developers or one interested in industrial applications of operations research.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This monograph presents a framework for optimum design of timetables to maximise schedule robustness and minimise resource deployment, especially for large railway networks, wherein the problem has been formulated as a multi-objective non-linear model. The monograph s contribution is the formulation of methods to reduce the problem size to computationally manageable proportions, and thus enable planners to undertake network-wide optimisation studies. The monograph demonstrates that the design of timetables can be spread over a canvas incorporating not only over the entire railway network, thus enabling study of the mutual interactions across the network, but also involving the optimisation of crew and rolling stock in the purview of the model. This can thus emulate the planning process more truthfully, wherein piecemeal optimisations are of little import. This monograph should be especially useful for researchers engaged in problems pertaining to railway networks, railway network planners, railway decision support software developers or one interested in industrial applications of operations research. 184 pp. Englisch. N° de réf. du vendeur 9783838338491
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This monograph presents a framework for optimum design of timetables to maximise schedule robustness and minimise resource deployment, especially for large railway networks, wherein the problem has been formulated as a multi-objective non-linear model. The . N° de réf. du vendeur 5414382
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